Add pipeline tag and link to code

Hi! I'm Niels from the community science team at Hugging Face.

I'm opening this pull request to improve the model card for ROSALIA. I've added the `image-text-to-text` pipeline tag to the metadata to improve discoverability on the Hub and included a link to the official GitHub repository.

README.md

@@ -1,15 +1,21 @@
 ---
 base_model:
 - xinlai/LISA-7B-v1
+pipeline_tag: image-text-to-text
 ---
 
 # ROSALIA-7B-v1
 
-**ROSALIA** is a vision-language model (VLM) designed for precise lesion segmentation in chest X-rays (CXRs).
+**ROSALIA** is a vision-language model (VLM) designed for precise lesion segmentation in chest X-rays (CXRs). It is a LISA model fine-tuned on the **MIMIC-ILS** dataset, a large-scale instruction-answer dataset for CXR lesion segmentation.
+
+ROSALIA is capable of **Instruction-Guided Lesion Segmentation (ILS)**, a medical-domain adaptation of referring image segmentation (RIS), allowing it to segment diverse lesions and provide textual explanations in response to simple, user-friendly instructions.
 
 This model is the core checkpoint of the paper:  
 **[Instruction-Guided Lesion Segmentation for Chest X-rays with Automatically Generated Large-Scale Dataset](https://arxiv.org/abs/2511.15186)**, accepted to **CVPR 2026**.
 
+- **Code:** [https://github.com/checkoneee/ROSALIA](https://github.com/checkoneee/ROSALIA)
+- **Paper:** [arXiv:2511.15186](https://arxiv.org/abs/2511.15186)
+
 ## 📖 Citation
 
 If you find this model or the related research useful, please cite our work:
@@ -20,4 +26,5 @@ If you find this model or the related research useful, please cite our work:
   author={Choi, Geon and Yoon, Hangyul and Shin, Hyunju and Park, Hyunki and Seo, Sang Hoon and Yang, Eunho and Choi, Edward},
   journal={arXiv preprint arXiv:2511.15186},
   year={2025}
-}
+}
+```